I don't use filters. I calculate the probability of a charge off event for every loan, compare it to the interest rate, and then generate a list of all loans available for investment ordered by expected profit. I have a threshold value where I would be willing to invest in any loan above a certain expected profit. Back testing this strategy suggests returns in the top 10% of any strategy I have come across and has a huge upside compared to a filter strategy: on any given day I could find dozens of loans in which to invest.
May I ask what you mean by "returns in the top 10% of any strategy"? What is the back-tested return and what time-period did you use for the back testing?
Would you mind sharing how you calculate the probability?
In order to calculate a probability wouldn't you need parameters such as "public records", "employment length", "number of credit inquiries", etc?
If so, wouldn't that be similar to creating multiple filters and applying them all to the available loans?
Filter 1 => 5 loans (ROI=16%)
Filter 2 => 10 loans (ROI=10%)
Filter 3 => 5 loans (ROI= 14%)
Total 20 loans and ROI = (5*16+10*10+5*14)/20=12.5%